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DO ELECTIONS SLOW DOWN
ECONOMIC GLOBALIZATION
PROCESS IN INDIA? IT’S POLITICS
STUPID !
Vadlamannati, Krishna Chaitanya
University of Santiago de Compostela
23 August 2008
Online at https://mpra.ub.uni-muenchen.de/10139/
MPRA Paper No. 10139, posted 25 Aug 2008 01:08 UTC
1
DO ELECTIONS SLOW DOWN ECONOMIC GLOBALIZATION PROCESS IN INDIA?
IT’S POLITICS STUPID !
Krishna Chaitanya Vadlamannati #
# University of Santiago de Compostela, Spain
ABSTRACT
I investigate whether timing of the elections impact economic globalization process or
not in India. In other words, do elections slowdown economic globalization process? The
theoretical underpinning is that, policies of economic globalization lead to economic and
social hardships in short run but benefit the economy in the long run. The motto behind
slowing down the economic globalization process before elections is that it leads to
polarization of voters and thus negatively affects the incumbent government. I make use
of Axel Dreher‘s economic globalization index and construct ‗instrumental electoral
cycle‘ to capture the scheduled and midterm election cycle.
Using time series data for India for the period 1970 – 2006, I find that scheduled
elections are associated with slow down in economic globalization, whereas midterm
elections are not. Replacing Dreher‘s economic globalization index with our modified
globalization index does not alter the results. I also find that slow down in economic
globalization process is responsive to the propinquity to a scheduled election year.
Meaning, as incumbent government nears the scheduled elections, economic
globalization process keeps slowing down, while this is exactly opposite during the early
years of incumbent government in office. These results suggest that elections generate
―electoral globalization cycle‖ in developing democratic country like India.
Keywords: Economic globalization; Election cycles; India
Acknowledgement: I would like to thank Arkadipta Ghosh, PhD candidate, Pardee RAND Graduate
School, USA and Dr. Artur Tamazian, Asst, Professor, University of Santiago de Compostela, Spain, for
their valuable comments while I was working on this paper. I also thank Dr. Dreher Axel for sharing the
economic globalization dataset with me. Remaining errors if any are mine.
2
1. Introduction In electoral competition framework, there are different models which talk about the effect
of elections on government behavior. The first such model, ‗political business cycle‘ was formulated by Nordhuas (1975) and Lindbeck (1976). They argue that politicians
manipulate the economic policies during the election period, by higher spending to
increase economic growth on one hand and on the other hand, the incumbent government
aims to keep the unemployment under control, leading to business cycles. While, Rogoff
& Sibert (1988) and Rogoff (1990) advocates ‗budget cycles‘ by increasing the spending
on consumption and reducing taxes before the elections to highlight that the incumbent is
competent enough to deliver public services. Recently, Khemani (2004) developed the
‗career concern‘ model in which she argues that pressure of elections will be higher on
politicians to provide better public services and increase developmental spending and
reducing non-developmental expenditure, highlighting that fiscal manipulation would be
low and selective on some of the taxes and spendings which directly effect the people.
All these studies deal with government policies with specific reference to fiscal policy.
However, instead of looking at only fiscal policies, I probe the effect of union elections
on economic globalization process in India. I undertake this investigation for two specific
reasons: one, since the advent of neoliberal policies in early 1990s in India, there is a
structural change in many of the government polices. There is a transformation from
‗inward looking polices‘ towards ‗outward looking or liberalized policies‘. These are driven by economic globalization process, which inturn affects basic government policies
like fiscal and monetary policies. Therefore, one can assume that economic globalization
process as a derivative of governments various economic policies. Two, the evidence on
the effects of economic globalization process on socioeconomic conditions is mixed and
hence its implications on elections are unknown. Thus, this study bridges this gap and
addresses several questions: Does incumbent government manipulate the economic
globalization polices just before the elections to avoid the defeat? Whether there exists
‗electoral globalization cycle‘? Do midterm elections affect economic globalization process? And what are the policy implications that we can derive from the results?
It is well proved fact that voters who are most hurt by the government policies which lead
to strained economic situations are more likely to punish the incumbent governments in
the elections (Burdekin, 1988; Lewis-Beck, 1991; Gleisner, R. F, 1992; Çarko lu, 1997;
Wilkin et al. 1997; Fielding, 1998 & 2000; Lewis-Beck & Paldam, 2000; Chappell &
Veiga, 2000; Lewis-Beck & Stegmaier, 2000; Youde, 2005; Nordhaus, 2006; Akarca &
Tansel, 2006a & b; Duch & Stevenson, 2006; Mitchell & Willett, 2006 and Veiga &
Veiga, 2006). Usually, voters relay more on the macroeconomic conditions of the country
while voting (Lewis-Beck, 1988), though certain elections are found to be issue based
elections. But in majority of the cases, it is the economic situation on the ground which
matters the most and is the driving factor for the voters (Alvarez et al., 2000). These
macroeconomic factors are inturn determined by the economic globalization policies
initiated by the incumbent governments. There is empirical evidence to show that
economic globalization policies lead to short term economic and social hardships, but
provide economic benefits in the long run (Wolf, 1999 & Vadlamannati, 2008). Because
the benefits of the economic globalization process tends to be isolated, but the costs
3
associated with it are strenuous in short run, those sections of the society who are worst
hit by these policies would like to replace the incumbent government with those who are
more likely to adapt policies which do not hurt the people. This forces the incumbent
government to slowdown the economic globalization process as and when they near the
scheduled election year. This would be the only option available with the government as
it cannot completely reverse the economic globalization policies which were adopted 10
to 15 years ago as reversal of these policies would prove very costly for the country.
Hence, economic globalization polices would accelerated once the incumbent
government gets back to the office post elections, thus creating ‗electoral globalization cycles‘. However, this is exactly opposite in the case of midterm elections. This is because the timing of midterm elections (which occur anytime after a previous election)
is unanticipated and hence, it does not provide incumbent government the scope to
manipulate and slowdown the economic globalization process.
Why India?
I selected India to conduct this study in the first place for several reasons. India happens
to be world‘s second largest developing country with a profound history of stable democracy. The Constitution of India allows the elections commission to conduct both
union and state legislative elections for every five year term. The union elections are
conducted for Lok Sabha (lower house of Parliament) once in five years. The
participation in union and state elections in world‘s second largest democracy is quite high. The average turnout in Union elections in India is about 58.7% (Election
Commission, 2004). India adopted the neoliberal economic policies in 1991 with a
Structural Adjustment Program with World Bank. Moreover, India provides classic case
of electoral globalization cycle as there were many instances where the incumbent
government was forced to go slow on such policies as and when it neared the elections.
In 1989 elections, the Congress government which introduced Economic Reforms
Commission did not even initiate the reforms process despite enjoying full majority in the
parliament. The Congress government after officially initiating neoliberal policies in
1991 almost halted the process as it neared 1996 Lok Sabha elections. Same is the case
with BJP led NDA government in 1996 and present Congress led UPA government. This
is because, though economic globalization process gave excellent economic growth in
long run, its real benefits are not reaching to the poor. Thus, many argue that India‘s economic growth and development process resulting from globalization policies is not
inclusive of the poor (Gupta, 1999). This is evident by comparing the growth in GDP and
Percapita GDP with the pace at which poverty and inequality levels are reduced. On one
hand, the rate of growth of reduction in poverty and inequality levels has been very low
during the last two decades (Dutta, 1991) and on the other hand, India witnessed rapid
surge in economic growth, industrial and services growth, urbanization and FDI inflows,
highlighting that the development process tends to be ‗exclusive‘. Therefore, India
provides an excellent case study to examine the existence of ‗electoral globalization cycle‘.
2. Election Cycles & Economic Globalization: Theoretical Underpinnings
4
The literature presents conflicting findings on the implications of economic globalization
process on socioeconomic development. The Liberal theorists argue that countries which
are highly engaged in globalization process are likely to experience higher economic
growth, greater affluence, more democracy, and increasingly peaceful conditions in the
home country and elsewhere (Flanagan & Fogelman, 1971; Weede, 1995; Jacobsen,
1996). It is believed that globalization process is most likely to improving quality of life.
It help promote economic development, providing trade and investment opportunities
creating much needed employment generation and reduce income inequality and poverty
thereby leading to decline in social unrest and economic insecurity. Thus, countries with
higher levels of globalization process should suffer lesser degree of socioeconomic
problems and have greater development. Higher globalization process also serves in
attaining development goals for developing economies.
On the contrary, skeptics contend that higher levels of globalization process tend to
generate greater economic and social inequalities. This leads to greater economic
insecurity and social unrest in the society. Sometimes it also paves way for the risk of
political instability and outbreak of riots, agitations, protests, conflicts and disturbances
thereby (Boswell & Dixon, 1990; Barbieri, 1996; Rodrik, 1997, Rodrik, 1998; Rodriguez
& Rodrik, 2000, Blinder, 2006; Summers, 2006; Krugman, 2007).
Taking both these perspectives into consideration evolves another set of group which take
middle path arguing that globalization brings both good and harm. Their premise is
largely based on the J-Curve model developed by Przeworski (1993) who advocated that
reforms and globalization policies though beneficial for the country and society in the
long run, they lead to economic and social hardships in the immediate short run. This
theory argues that whatever might be the long-term implications of socioeconomic
growth and high development, the immediate short term effect of economic globalization
process is the structural adjustments in the economy which generates substantial
economic and social costs in terms for increase in unemployment and inflation (Marer &
Zecchini 1991), resource misallocation (Roland 1994), volatility in income distribution
(Milanovic 1995), declining output (Kolodko 1999), and poor socioeconomic conditions
(DeMelo, Denizer, & Gelb 1996). There are also other prominent studies like Wolf
(1999) finds a significant J-curve relationship between neoliberal policies and economic
growth and development. Similar such findings were apparent in the study related to
reforms and globalization process and its impact on government repression by
Vadlamannati & Soysa (2008). With specific focus on India, Vadlamannati (2008) finds
similar such J-curve relationship between economic reforms and globalization with
poverty levels, suggesting that economic globalization and internal reforms are associated
with economic and social hardships in the short run, but are beneficial in long run1.
To control these economic and social costs in short run, sometimes the government
resorts to policies which can be detrimental to the sizeable sections of the society. For
example, to curtail high inflationary pressures, on one hand, the government hikes tax
rates and on the other hand it can also increase interest rates. Similarly, in the process of
1 Similar such results are found by Vadlamannati & Irala (2008) for economic reforms and domestic private
investments in India.
5
making the public sector efficient and improve the savings of public sector, government
undertakes massive restructuring policies like privatization program which many times
results in huge layoffs. To contain higher levels of fiscal deficits, the governments due to
their coilation political compulsions resort is cutting the social sector development
expenditure. Such hard policies interned for long-term benefits make a sizeable fraction
of the population disaffected (Mygind 1999). Thus, the incumbent governments who
implement these neoliberal policies face severe pressures from those groups and sections
in the society which are widely affected by these liberalized economic policies. This
creates short-run losers from economic globalization policies as the major opposers of
government‘s neoliberal economic policies. Their main argument is that they do not
believe the idea of the government which promises future gains and in return expecting
political support to carry forward the neoliberal economic policies. Further, they believe
that government often fails to keep the commitment which is made to the people during
the previous elections that they would continue with the economic globalization polices
until it yields benefits to the society in the long run2 (Slantchev, 2005). Moreover, Rodrik
(1994) argues that the consequences of neoliberal policies often involve the redistribution
of income among different groups. If the efficiency gains from those policies are not
substantial and income is not redistributed properly, this leads to either evade or slowing
down of those policies. Precisely this is the reason why whenever the new form of polices
are designed and adopted, there would be wide spread agitation to resist making
substantial policy changes which inturn affect the vast sections of the population. This
sometimes leads to angry mob protests, conflicts, strikes and lockouts and riots forcing
the governments to roll back or reverse the policy decisions (Fields, 2003). This also
means that governments that are vulnerable to the reactions of certain sections of the
society, which constitute significant portion, are less likely to carry forward the economic
globalization process at a rapid pace and might engage in piece meal reform process.
According to the electoral competition theories the opportunistic politicians resort to
manipulate economic policies during election times for political gain. Thus keeping the
country‘s long term economic benefits on stake by manipulating the economic policies to reduce short term political losses (avoiding loosing elections). Infact the ‗political business cycle‘ theory is propounded by Nordhaus (1975) and Lindbeck (1976) argue that
usually the incumbent governments keep growth high and unemployment low just before
elections. To gain from these manipulations, the incumbent governments bank on
uninformed voters who can provide them short term benefits. This model finds support in
many studies in literature specially related developing countries. Studying the case of
eight Latin American countries, Ames (1987) finds evidence of increased public spending
during election years. Schuknecht (1996) examines fiscal policies in a sample of 35
developing countries from 1970 to 1992. He finds that while there is no election effect on
2 Sometimes as in the case of India, due to various political compulsions like coalition & regional politics,
the governments are forced to sacrifice the reforms process. The best example could be the halt of
privatization process in India by the UPA government in 2002 due to pressures from its allies. Keeping
away the Bills on Insurance, Banking and allowing Retail FDI reforms due to pressure from Left Front, a
key ally supporting the UPA government from outside the parliament. Promises are often made by the
incumbent governments in India to bring labour reforms. But these reforms are not even initiated by any
government fearing political backlash. There are numerous such examples in Indian context to show the
backtracking from the promises made by the governments during the elections period to its public.
6
real output, there are election-related expansions and reductions of the fiscal deficit by
almost 0.7% of GDP. In an another study by Schuknecht (1999) finds for developing
countries, that governments resort to expansionary fiscal policies to improve their
chances of re-election.
Moyo (1999) finds evidence of electoral cycles in public savings for a sample which
includes both developed and developing countries. The study by Shi & Svensson (2000)
examines fiscal policy electoral cycles for both developed and developing countries.
They find evidence of political business cycles in government consumption and the fiscal
deficit in a Rogoff-style model, with cycles of greater magnitude in developing countries.
Testing the same, Block (2002) presents cross-country evidence of political business
cycles for African countries. Using five monetary and fiscal instruments, his findings are
consistent with the predictions of rational opportunistic political business cycle theory. In
a regional study on India by Chaudhuri & Dasgupta (2005) finds that there is an increase
in current expenditure and decline in developmental spending during the election years3.
Contradicting these arguments, Khemani (2004) developed new model of ‗career concerns‘ in which she argues that during the election years, there is a significant improvement in public services and political manipulation of all kinds of polices do not
find support. Only development spending (capital expenditure) tends to increase, while
nondevelopment spending (current expenditure) reduces. Nevertheless, these models
demonstrate the manipulation of incumbent governments to persuade voters before the
election period and thereby generate electoral cycles.
Figure 1: ‘Electoral Globalization Cycle‘
Taking into account the earlier discussions on socioeconomic implications of economic
globalization process and electoral cycles, I believe that a government that is responsive
to its voters in the country is more likely to slowdown the economic globalization process
3 There are also studies which have found contradicting results. For example, see: Golden Poterba (1980);
Alesina & Roubini (1992); Besley & Case (1995); Reid (1998).
Economic
Globalization process
Years from scheduled election date
(Scheduled election year = 0)
0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0
7
as the government nears scheduled elections. But the same responsive government once
the takes over the office soon after the elections as an incumbent, is more likely to
accelerate the economic globalization process. This brings us to our first two
propositions:
Hypothesis 1 (H1): Slowdown in economic globalization policies are associated with
scheduled election years.
Hypothesis 2 (H2): Slowdown in economic globalization policies is greater as
incumbent government nears scheduled election year.
Based on the first two hypotheses, I assume that there is an ‗electoral globalization cycle‘ which basically means slow down in economic globalization process is responsive to the
propinquity to a schedule election year. Meaning, as incumbent government nears the
schedule elections (election year being 0 in figure 1), economic globalization process
keeps slowing down, while this is exactly opposite during the early years of incumbent
government in office.
Here it is very important to make a distinction between scheduled elections and midterm
elections. In Indian context, scheduled elections are those which are constituted by
elections commissions based on Constitution of India for every five years. Whereas,
midterm elections are those that occur one, two, three or four years after the previous
election (either scheduled or midterm), that is, before the completion of the five year term
of the elected government in office. Therefore, this distinction between the two becomes
even more important to globalization policy choices because the timing of midterm
elections is usually sudden and unanticipated. So it is not reasonable to expect incumbent
governments to slowdown globalization policies to influence election outcomes. This
leads to our final proposition:
Hypothesis 3 (H3): Slowdown in economic globalization policies is NOT associated
with midterm elections because of the unanticipated and uncertain timing.
Each of these hypotheses is examined in the empirical analysis which would follow this
section. The rest of the paper is organized as follows: Section 3 deals with research
design with specific focus on measuring economic globalization process, creating
instrumental electoral cycles for both scheduled and midterm elections, followed by data
sources and identifying the empirical strategy to be employed. Section 4 presents
discussion on the results derived from our empirical analysis. Final section concludes the
study and highlights the scope for further research avenues.
3. Research Design
3.1. Measuring Economic Globalization: Why Dreher’s Index?
There is a vast amount literature on estimating the effects of globalization on growth,
development, poverty, inequality and so on. In all these studies globalization is measured
8
only partially with one or a few economic variables like the trade ratio, direct foreign
investment, total capital flows, monopolization of exports, black market premiums and
country specific globalization dummies etc. Such measures are generally known as
openness of the economy. Subsequently more comprehensive measures of globalization
were developed with the weighted average or principal components methods. The well
known Sachs & Warner (1995) binary index of openness is based on the weighted
averages of some economic variables. Others, while accepting economic variables are
important to measure economic globalization, argued that brining them under one
umbrella was the major task. The well known Lockwood & Redoano (2005) discrete
index of economic globalization from 1980-2004, is based on a few such economic
variables. Similarly, Kearney, Andersen & Herbertsson (2005) using trade and finance
variables have also developed such indices for 62 countries starting from 2000, to
determine the annual rakings of countries using Kearney index.4 In practice it is hard to
maintain a distinction between openness which is proxied mostly with economic
variables and economic globalization, which is much beyond just measuring trade
openness. Thus the question to be addressed is how economic globalization should be
measured.
We do not take into consideration both the indices mentioned above for various obvious
reasons. First, Lockwood & Redoano (2005) globalization index covers only trade and
other economic variables ignoring some of the most important facets of economic
globalization: tariffs, restrictions and quotas. Thus, this index without these important
measures becomes just another simple proxy like trade openness variable. Second, with
respect to Kearny index, as highlighted by Rao et al. (2008), their weighting scheme is
somewhat arbitrary in that they do not adjust for the size of the country on the basis of its
population. Third, it is not possible to use both Kearney, Andersen & Herbertsson (2005)
and Lockwood & Redoano (2005) indices in time series regressions because of the
absence of time series data.
In light of all these observations, Axel Dreher (2006) is a welcome contribution because
his comprehensive measures of globalization will help to decrease many disagreements
on the measurement issue. Mainly Dreher‘s globalization index is formulated for 123
countries from 1970 to 2005 and recently updated. His overall globalization index
includes three sub indices from the economic globalization, social globalization and
political globalization; see Section 2 in the study of Dreher (2006) for details5. This is
beyond the scope of this study to use the comprehensive globalization index. Rather, our
focus is on economic globalization.
I select Dreher‘s economic globalization index simply because it overcomes all the three disadvantages highlighted above. The Dreher economic globalization index combines
4 Using mainly economic variables are: Edwards (1998), Dollar & Kraay (2004). Rodrick (1997), Crafts
(2000), Bordo & Meissner (2007) & Rincon (2005) found that globalization positively affects growth.
Chanda (2001) used capital account openness as proxy for globalization to find that it does not help
developing countries in growth, while Alesina et al. (1994) find the opposite. Using FDI as proxy for
globalization, Zhang (2001), Campos & Kinoshit (2002), Alfaro (2003), Chowdary & Mavrotas (2006) and
Hansen & Rand (2006) find that globalization has positive effects on growth. 5 These indices can be downloaded from http://globalization.kof.ethz.ch/
9
many economic indicators which also includes ‗trade and investment restrictions‘ like:
hidden import barriers, mean tariff rates, taxes on international trade (percent of current
revenue) and capital account restrictions, which no other indices captures as
comprehensively as Dreher‘s index. Of course, the other indicator in this index includes
‗actual flows‘, which captures: income (percentage of GDP); volume of trade (percentage of GDP); FDI inflows and inflows stock (percentage of GDP) and Portfolio investments
(percentage of GDP). The other advantage of Dreher‘s index is methodological as it uses widely available technique of the principal components method and Dreher index is most
suitable for time series study as it dates back to 1970.
3.1. i. ‘Modified’ Economic Globalization Index
The Dreher‘s economic globalization index is measured on 0 – 100 scale, 0 meaning no
or low economic globalization, while a score of 100 means full economic globalization.
Sometimes, there can be problems while using this index as dependent variable. Since the
economic globalization index coefficient is bounded between 1 and 100, using Ordinary
Least Squares (OLS hereafter) regression might sometimes be problematic. This is
because, often OLS assumes that the dependent variable to be unbounded. Thus, to
counter this problem we follow Reuveny & Li (2003) method, which is a usual practice
to transform the bounded variable into unbounded indicator. I transform the economic
globalization index into unbounded measure by using the following formula:
Unbounded Economic Globalization Index =
I however, make use of this unbounded transformed economic globalization index to
assess the robustness of the main results.
3.2. Constructing Instrumental Electoral Cycles
The need for constructing instrumental electoral cycle arises from the question whether
timing of elections are endogenous to economic globalization process carried by the
respective incumbent governments. Theoretically speaking, this may not be true because
in India, union elections are fixed on five year basis. The constitution of India allows the
elections commission to conduct union elections once in five year period. However, over
the period of time, especially from 1980s, India also witnessed quite a few midterm union
elections. These occur due to various reasons which include drifting away the Member of
Parliament from ruling alliance, political instability because the governments sometimes
do not possess the required numbers to prove its majority in the parliaments, shifting of
political alignments within the alliance group and so on. Infact in our sample from 1970
to 2006, out of total 10 union elections, 5 happens to be midterm elections and rest are
schedule elections. This means exactly 50% of the total union elections in our sample
period are marked by midterm elections. The exact timing of these midterm union
elections is sudden and unanticipated. Since these events are unexpected, it might not
lead to slow down in economic globalization process, as the incumbent government
Economic Globalization Index
100 – Economic Globalization Index
10
would not have ample time to plan and react to these midterm elections. One possible
solution to address this problem is to distinguish between the effects of scheduled union
midterm elections on the outcome of interest – economic globalization process. To this
end, I employ the technique of Khemani (2004) in constructing what is called as
―instrumental electoral cycle‖ for both schedule and midterm elections.
Figure 1: Schedule election cycle
Years Note: SE= Schedule Elections
The schedule election cycle is the one which follows a 5-year cycle and is renewed after
every schedule election year, that is, it again begins with 4, 3, 2 and 1. The figure 1 best
captures coding of this cycle.
Figure 2: Midterm election cycle
Years Note: SE= Schedule Elections; MT= Midterm Elections
The midterm election cycle also follows a 5-year cycle, but it is also renewed after every
midterm election. Many times, the scheduled elections coincide with election years in
midterm election cycle. The midterm election years are treated to be 4, 3, 2, 1 year before
a scheduled election year. The year after any midterm election is again coded as 4 years
before a scheduled election followed by 3, 2 and 1. The timeline of the midterm election
cycle is captured in figure 2.
In our sample as highlighted earlier out of 10 election years, 5 are midterm elections
which took place in 1980; 1984; 1991; 1998 and 1999. Amongst them, the high
frequency political volatility period is a constant feature during post 1990s. Based on
these discussions, we formulate the empirical model to estimate the direct effect of the
electoral cycle on economic globalization polices of the incumbent government:
……………………………… (1)
SE 4 3 2 1 SE 4 3 2 1 SE 4 3 2 1 SE
SE 4 3 MT 4 3 2 1 SE 4 MT 4 3 2 1 SE
4 4
EGt = 1 + Σ 2 SECŦ
t + Σ 3 MTCŦ
t + 4 EGt-1 + εt
ф=1 ф=1
11
Where: t = time; = Intercept for the equation; = Regression Coefficients for variable
―n‖; ε = error term for country at time ―t‖. The hypothesis variables presented here are:
SEC = Schedule election cycle; MTC = Midterm election cycle and Ŧ = 1, 2, 3 & 4 for
respective electoral cycles. This means for example: SEC0
t is 1 if t is a scheduled election
year in India; SEC1
t is 1 if t is one year before a scheduled election year; SEC2
t is 2 if t is
two years before a scheduled election year; SEC3
t is 3 if t is three years before a
scheduled election year and SEC4
t is 4 if t is three years before a scheduled election year
in India.
The results from above specification (1) may suffer from omitted variable bias due to
absence of other control variables. Thus, the same equation is also estimated including
some observable country characteristics CVt, including economic growth rate (GDP
growth rate), economic development (proxied by log Percapita GDP), political
constraints of the ruling government using political constraints index, official poverty
rate; income inequality measured by Gini index and economic & political crisis dummy,
which coded 1 if there is any economic and political crisis and 0 otherwise as control
variables. The data for all these control variables comes from World development
indicators (2006). This model allows to tests key hypothesis in this paper, which is:
scheduled elections have a significant negative effect on economic globalization, but
midterm elections do not. Thus, using these control variables, equation (1) would
therefore be modified as follows:
……………………………… (2)
To capture the effects of distance from election years on globalization process, we
developed ‗full election cycle year dummies‘. We formulate four dummy variables namely: 4-years before elections variables which take the value of 1 in the 4
th year before
every schedule election year and 0 otherwise. The second dummy includes 3-years before
elections variable which has the value 1 in the 3rd
year before every schedule election
year and 0 otherwise. The third dummy variable is 2-years before elections variable
include the value of 1 in the 2nd
year before every schedule election year and 0 otherwise.
Finally, 1-year before elections variable takes the value of 1 in the 1st year before every
schedule election year and 0 otherwise. These variables allows to measure how the
temporal distance from a scheduled election year affects economic globalization process
vis-à-vis an election year. The model is specified as follows:
……………………………… (3)
Where, Dey1, 2, 3, 4…are the distance from election year dummies. This empirical
analysis covers the period 1970 to 2006 for India. The time-series data may exhibit
4 4
EGt = 1 + Σ 2 SECŦ
t + Σ 3 MTCŦ
t + 4 CVt + t
ф=1 ф=1
4 4
EGt = 1 + Σ β2 SECŦ
t + Σ β3 MTCŦ
t + β4 CVt + β4 Dey1t + β4 Dey2t + β4 Dey3t + β4 Dey4t + t ф=1 ф=1
12
Heteroskedasticity and serial correlation problems as they often tend to cause biased
standard errors for coefficients, producing invalid statistical inferences. To deal with
these problems, we estimated for all the models the Huber-White robust standard errors.
These estimated standard errors are robust to both Heteroskedasticity and to a general
type of serial correlation (Rogers, 1993 and Williams, 2000). Additionally, to confirm the
results do not suffer from serial correlation, we also perform Breusch-Godfrey Serial
Correlation LM Test.
4. Empirical Results & Estimates
4. 1. Descriptive Statistical Analysis
The sample of years that we examine in total make up of 37 observations. In Annexure
1, we present summary statistics for this sample for all the variables that we employ in
the regression analysis. The mean value for number of economic globalization index is
22.00 per-years with a large standard deviation of roughly 9.07. Regarding GDP growth
rate we can find that the median growth rate is 5.63%. Moreover, the variance in GDP
growth rates is fairly low, with a standard deviation of 3.01% and growth rates ranging
from –5.24% to 9.86%. With respect to percapita GDP, the mean value is log 5.72 with a
standard deviation of just log 0.35. The statistics for Poverty rate and Gini index are
frightening. The mean value for the both is 39.55% and 32.86% respectively. These
numbers are significantly higher by any international standards. While the maximum
value for Poverty rate is 56.00% and 38.00% for Gini index, the minimum value is
22.00% and 29.17% respectively.
In Annexure 2 we present the information about the swing and the degree of swing in
economic globalization index during schedule election years in India covering the sample
period. We classified the swing, which is net change in the economic globalization index
in schedule election year to previous year, under four categories. These include: decline;
marginal increase; gradual increase and greater increase. These categories are arrived by
using simple bifurcation of swing numbers which states that when the percentage change
of index from current year (election year) to previous year is negative and or zero, then it
is classified as decline. Similarly, when the percentage change in the index is in the range
of 0.01 – 0.1, then it is called marginal increase phase. When the change in index ranges
between 0.2 – 1.0, it is known to be gradual increase phase and when the index range
from 1.1 and above, it is termed as greater increase. Using this simple methodology, we
find in annexure 2 that out of seven schedule election years in the period of 1970 to 2006,
three times, there as decline in the economic globalization index growth. Once there was
marginal increase which was during 1996 amidst political crisis and uncertainty, which is
decimal. Twice there was gradual increase in 1984 and 1989, which was the era of single
party dominant governments. But only once, we could see a greater increase in index,
which was in 2004. This tells us that there is certainly some impact of scheduled elections
on the slowing down of globalization index in election years, though it is not as
comprehensive as we would have expected.
13
4. 2. Regression Estimates
The results of regression estimates in assessing the impact of schedule and midterm
electoral cycle on economic globalization process in India are presented in table 1 and 2
(models 1 to 7). Addressing the problems of serial correlation and multicollinearity,
specific tests are conducted and the results are displayed at the end of the each model in
table 1 and 2. Further, the results of robustness check and sensitivity analysis are
presented in annexures 4; 5 and 6. We also control for the problem of Heteroskedasticity
using White Heteroskedasticity-consistent standard errors & covariance.
The regression results confirm the hypothesis offered on electoral cycles in economic
globalization in the Indian context. Specifically, the results from the both the equations (1
& 2) show that schedule elections have a significant negative effect on the economic
globalization process. Concentrating on results of equation 1 indicates the direct
relationship between economic globalization process and electoral cycle. The coefficients
reported in model 1 (table 1) indicate that the presence of schedule election year is
leading to decline in economic globalization index by 0.28% with 10% statistical
significance. Several studies include a lagged dependent variable to control for
autocorrelation. A lagged dependent variable is also meant to control for the spill-over
effects (Neumayer, 2005). There are two reasons for the inclusion of a lagged dependent
variable specifically in this model. First, a methodological reason, that is to control for
autocorrelation, endogenity, and omitted variables (Beck & Katz, 1995). Second, a
theoretical reason, that holds that governments tend to use past decisions as a baseline for
their present decisions.
Table 1: Elections & Economic Globalization equation function
Dependent variable: Dreher‘s Economic Globalization Index
Variables Model 1 Model 2 Model 3
Constant
-0.18
(0.63)
-1.06 +
(0.76)
-0.36
(0.86)
Schedule Election year
-0.28 ***
(0.15) ------ -0.28 ***
(0.16)
Mid-term Election years ------ 0.09
(0.15) 0.07
(0.15)
Economic Globalization (t-1)
1.08 * (0.03)
1.08 * (0.02)
1.07 *
(0.03)
R-squared 0.986029 0.984817 0.986110 Adjusted R-squared 0.985183 0.983897 0.984808 Durbin-Watson statistic 2.198445 2.151341 2.228900 Log likelihood -53.24673 -54.74492 -53.14216 F-statistic 1164.544 1070.222 757.2849 Breusch-Godfrey Serial Correlation LM Test
F-statistic 0.719393 0.359689 0.868890
Probability. F 0.4026 0.5529 0.3585
14
Total number of Observations 37 37 37 Note: * Significant at 1% confidence level; ** Significant at 5% confidence level *** Significant at 10%
confidence level; + Significant at 15% confidence level. The models are controlled for Heteroskedasticity.
White Heteroskedasticity-Consistent Standard Errors are reported in parenthesis.
The results of lagged dependent variable show 1% significant and positive relationship.
This suggests that governments tend to use past decisions as a baseline for their present
decisions. Using lagged dependent variables, we were also able to counter the problem of
auto correlation6. In model 2, we replaced schedule elections cycle with the midterm
election cycle. We found that it is neither negative nor significant, suggesting that
midterm elections do not have any impact on slowing down of economic globalization
process because of the uncertainty of occurrence associated with such elections. In model
3, we introduced both schedule and midterm election cycles and found that schedule
election cycle having 10% significant and negatively associated with economic
globalization process, while once again, we could not find any such relationship with
midterm electoral cycle.
In all the three models (in table 1), we use lagged dependent variable, which help
improve Durbin-Watson (DW hereafter) statistic and counter autocorrelation problem. To
confirm the non existence of serial correlation problem, we also perform Breusch-
Godfrey Serial Correlation LM Test (results shown at the end of table 1). We found that
the all the models are free from the problem of serial correlation. But these results might
suffer from omitted variable bias. Also, these results should be validated by including
some of the important socioeconomic variables which formulate key determinants of
economic globalization process. A step in this direction is the results captured in model 4
to 7 in table 2. Another prominent feature of this model is that we also capture the full
cycle of schedule elections using distance from election year dummies highlighted in
equation 3.
Table 2: Elections & Economic Globalization equation function
Dependent variable: Dreher‘s Economic Globalization Index
Variables Model 4 Model 5 Model 6 Model 7
Constant
-248.52 *
(19.23)
-246.69 *
(24.41)
-255.32 *
(26.29)
-250.46 *
(17.52)
Schedule Election year
-0.49 **
(0.21) ------ ------ -0.69 *
(0.22)
Mid-term Election years ------ -0.24
(0.25) ------ ------
1 year before Elections
------ ------ 0.42
(0.71)
0.30
(0.65)
2 years before Elections ------ ------ 0.97 ***
(0.59) 1.59 *
(0.52)
6 We first ran these results without lagged dependent variables. We obtained DW stat of 0.80 value. After
using the lagged dependent variable, we the DW stat significantly improved.
15
3 years before Elections
------ ------ 0.69 +
(0.48)
0.05
(0.54)
4 years before Elections
------ ------ 0.09
(1.24)
-0.62
(0.89)
Log (Economic Development)
41.38 * (3.05)
41.28 *
(3.72)
42.34 *
(4.19)
41.30 *
(2.91)
GDP Growth rate
-0.27 * (0.08)
-0.26 *
(0.09)
-0.28 *
(0.09)
-0.29 *
(0.08)
Political Constraints Index
-4.93 +
(3.38)
-6.16 +
(4.12)
-5.12
(3.70)
-4.20
(3.26)
Poverty Rates 0.63 * (0.08)
0.61 * (0.11)
0.65 * (0.11)
0.64 * (0.08)
Gini Inequality
0.41 * (0.14)
0.39 ** (0.14)
0.39 **
(0.15)
0.47 *
(0.13)
Economic & Political Crisis
-1.35 *** (0.82)
-0.80
(0.79)
-0.81
(0.81)
-1.60 **
(0.76)
R-squared 0.982914 0.980214 0.980935 0.986617 Adjusted R-squared 0.978790 0.975438 0.973602 0.980728 Durbin-Watson statistic 1.823487 1.524448 1.584861 2.099284 Log likelihood -58.28612 -61.00085 -60.31421 -53.76759 F-statistic 238.3342 205.2402 133.7747 167.5486
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.187697 1.771908 1.130441 0.245338
Probability. F 0.6682 0.1939 0.2978 0.6249
Total number of Observations 37 37 37 37 Note: * Significant at 1% confidence level; ** Significant at 5% confidence level *** Significant at 10%
confidence level; + Significant at 15% confidence level. The models are controlled for Heteroskedasticity.
White Heteroskedasticity-Consistent Standard Errors are reported in parenthesis.
The coefficients of schedule elections reported in model 4 of table 2 indicate that
schedule election years are strongly associated with decline in economic globalization
process. We find that for every single election year, the economic globalization index is
reduced by 0.49%. Infact adding control variables lifted the statistical significance level
of this variable to 5%. These results remain consistent across the board. In the model 5,
we replace schedule elections with midterm electoral cycle. We find that though it has
negative sign, it remains statistically insignificant, suggesting that midterm elections
necessarily need not result in slow down of economic globalization process. We present
full election cycle using distance from election year dummies in model 6 (see table 2).
The results show some interesting findings. We find that all the variables, 4, 3, 2, and 1
year distance from election year is positive. But the coefficient values of these variables
show some interesting trends. I find that economic globalization process would increase
by just 0.09% during the first year of incumbent government in office. This increase is
0.69% during the second year of incumbent government in office. While, economic
globalization process increase by more than 0.97% in the third year of incumbent
government in office, but then it decreases by 0.45% in the fourth year in office,
registering an insignificant increase in economic globalization index of 0.42% in the year
before a scheduled election. This goes down even further in the election year resulting in
16
negative effect on economic globalization process. The coefficients plotted in graph 1
(see annexures) clearly depict a ‗cyclical movement‘ in carrying out the economic globalization process by the incumbent governments. The graph shows a perfect inverted
U-shaped kind of relationship between schedule elections and economic globalization
process. We also estimated this equation by including schedule election variable with
these full electoral cycle dummies (see model 7; table 2). We found almost similar such
relationship between schedule elections and economic globalization process. The
coefficients of this model are also captured in graph 2 (see annexures). These results
confirm all the three hypothesis, H1; H2 & H3.
Within the control variables, we find that improvement in economic development has a
greater positive influence on economic globalization process. Holding at its mean value,
increase in economic development by its highest value (log 6.45) would increase
economic globalization index by 41.38%. Strangely, we find opposite results with respect
to economic growth. But, the coeffient value of the later is much lesser than that of
former. With respect of socioeconomic variables, we find both poverty rate and income
inequality (Gini) index are positively associated with economic globalization process. A
1% increase in both, increases economic globalization index by 0.61% and 0.41%
respectively. The other political variables include, political constraints index, which is
negatively associated with economic globalization process. Though this relationship is
weak at 15% significance, increase in this variable lowers economic globalization index
by 4.93%. While, for every economic and political crisis there is a corresponding decline
in economic globalization index by 1.35%. Despite inclusion of these key control
variables, our main hypothesis variables results do not alter. We also report correlation
matrix in annexure 3. One can observe that there is no significant multicollinearity
problem, though in couple of cases (poverty, inequality & economic development) the
correlation is quite high. Also, the DW stat show fairly good results, but to ensure that the
model do not suffer from serial correlation problem, we perform Breusch-Godfrey Serial
Correlation LM Test (results shown at the end of the table 2). The results of the test
confirm the absence of serial correlation problem.
4.3 Robustness Check
We wanted to breakdown the sample into two periods, pre and post reforms period7 to
reconfirm these results. However, we could not do so because we were handicapped
because the total sample period was very short and we could not breakdown into two
periods as the results would be biased and not longer be valid. Despite this, we ran
several tests of sensitivity. First, we ran the results by introducing schedule election year
along with each of the full election cycle variables separately. The results are captured in
annexure 4. The results show that schedule election variable in all models from 8 to 11
remains negatively significant. Despite introducing each full election cycle dummy
variables separately, the results of schedule election year remain intact. Despite
introducing election variables separately, we could still trace an inverted U-shaped curve
on the coefficients of these variables. The results are also free from serial correlation
7 The official economic reforms program in India was started in 1991 with the help of World Bank‘s
Structural Adjustment Program.
17
problem as indicated by Breusch-Godfrey Serial Correlation LM Test. Second, in the
next two models (12 & 13) captured in annexure 5, we introduced number of strikes and
lockouts variable. This captures the anti-globalization protests. We witness that the main
hypothesis variables results to be perfectly stable. Even in this case, we can see an
inverted U-shaped curve on the coefficients of elections variables.
Third and the final robustness check include performing sensitivity analysis, this time by
changing the dependent variable. We replace Axel Dreher‘s economic globalization index with our own ‗modified economic globalization index‘. The results are captured in annexure 6. We find that despite the change in dependent variable, the schedule election
year variable has 5% significant negative effect on economic globalization process.
While, consistent with our earlier findings, we could not find any statistical significant
impact of midterm elections on economic globalization. It is also worth noting in models
16 and 17 (annexure 6) that full election cycle variables depict the trend of inverted U-
shaped relationship with economic globalization process. Despite performing several
robustness checks, we could gather three important findings. These include: one,
schedule elections year significantly reduces economic globalization process. Two, there
is no impact of what so ever of midterm elections on economic globalization process and
finally, there is a clear U-shaped relationship between full election cycle and economic
globalization process, suggesting that as incumbent government nears the schedule
elections, economic globalization process keeps slowing down, while this is exactly
opposite during the early years of incumbent government in office.
5. Conclusion & Summary
Literature on political competition demonstrates how incumbent politicians might
manipulate economic policies to persuade voters before an election, and thereby generate
political budget cycles (Nordhuas, 1975; Lindbeck, 1976; Rogoff & Sibert, 1988; Rogoff,
1990; Khemani 2004 and Chaudhuri & Dasgupta, 2005). There are similar such studies
with specific reference to India (Karnik, 1990; Sen & Vaidya, 1996; Khemani, 2004 and
Chaudhuri & Dasgupta, 2005) but are generally related to fiscal policies. We extend this
to the economic globalization polices adopted by the central governments in India. We
formulate ‗electoral globalization cycle‘ based on the premise that globalization process leads to short run losses but benefit the economy in long run. Because the benefits of the
economic globalization process tends to be isolated and costs associated with it are
strenuous in short run, those sections of the society who are worst hit by these policies
would like to replace the incumbent government with those who are more likely to adapt
policies which do not hurt the people. This often forces the incumbent government to
slowdown the economic globalization process as and when they near the scheduled
election period. Based on this theory, we offered and tested three related hypotheses on
electoral cycle related to economic globalization process.
Using time series data on elections and Axel Dreher‘s economic globalization index, it demonstrated that economic globalization process responds to the timing of union
elections in India. While there was a strong electoral cycle in economic globalization
process, which experienced a marked decline in election years, the impact of midterm
18
elections is insignificant. This is perhaps due to its timing which is uncertain and
unanticipated which gives no scope of the incumbent governments to slow down the
economic globalization process. The results portrayed in the paper are strongly valid as
we have nullified the problems of serial correlation and multicollinearity. We also
addressed the issue of bounded dependent variable and converted the same into unbound
variable. The results do not change using this unbounded economic globalization index.
Thus, an incumbent‘s varying degree of concern for slowing down the globalization
process for its short term political gains and fear against loosing the elections increases as
the union elections draw nearer - does seem to be a plausible hypothesis, and is well
supported by the results in this paper. This is best exemplified by the estimated
instrumental electoral cycle for economic globalization process wherein both the
globalization process tend to increase during the earlier years of an incumbent‘s tenure in office, and decline in as scheduled elections draws near. Further, the statistically
insignificant effect of midterm elections on the economic globalization process also
provides evidence in favor of the hypotheses offered in this study.
Implications of the results & where do we go from here?
The results in this paper highlight three important points. First, these results show that
electoral cycles are not necessarily confined to fiscal and monetary policies alone. Rather,
it can affect the most important policies like economic globalization process, which
inturn drives various policies of the governments (like fiscal, monetary, public sector
etc). Second, these results also suggest that elections can indeed act as a disciplining
device for incumbent governments in the hands of the losers in the short run to influence
the fate of the incumbent governments to halt the neoliberal policies. Finally, the effect of
political manipulation of economic globalization policies by the incumbent governments
shows how politicians are only concerned to maximize their short run political gains at
the expense of minimizing the long run economic benefits generated from higher levels
of economic globalization process. Taking these results into consideration, our next
interesting step would be to probe whether similar such results can be replicated using
time series cross sectional analysis for other democratic countries in the world.
19
Annexures
Annexure 1: Descriptive Statistics
Economic
Globalization
GDP
growth rate
Log
(Percapita GDP)
Political
Constraints
Poverty
rate
Gini
Index
Schedule
Elections
Mean 22.00 5.18 5.72 0.44 39.55 32.86 2.14
Median 15.94 5.63 5.68 0.42 39.00 31.88 2.00
Maximum 44.00 9.86 6.45 0.58 56.00 38.00 4.00
Minimum 14.60 -5.24 5.29 0.29 22.00 29.17 1.00
Standard Deviation 9.07 3.01 0.35 0.08 10.45 2.68 1.18
Probability 0.04 0.00 0.23 0.45 0.28 0.08 0.14
Sum Sq. Dev. 2960.65 326.89 4.38 0.21 3928.47 259.58 50.32
Observations 37 37 37 37 37 37 37
Mid-term
elections
Economic &
Political Crisis
1 year before
elections
2 years before
elections
3 years before
elections
4 years before
elections Mean 2.51 0.13 0.16 0.14 0.11 0.11
Median 3.00 0.00 0.00 0.00 0.00 0.00
Maximum 4.00 1.00 1.00 1.00 1.00 1.00
Minimum 1.00 0.00 0.00 0.00 0.00 0.00
Standard Deviation 1.17 0.35 0.37 0.35 0.32 0.32
Probability 0.20 0.00 0.00 0.00 0.00 0.00
Sum Sq. Dev. 49.24 4.32 5.03 4.32 3.57 3.57
Observations 37 37 37 37 37 37
Annexure 2: Economic Globalization during Election years
Sl. No.
Schedule
Election year
Swing in Economic
Globalization Index
Net change in Index {t - (t-1)}
1 1970 Decline 0
2 1977 Decline -0.1
3 1980 Decline -0.1
4 1984 Gradual Increase +0.21
5 1989 Gradual Increase +0.71
6 1996 Marginal Increase +0.05
7 2004 Greater Increase +1.6 Note: t = current years; Decline = negative change in index in t from t-1; Marginal increase in change in
index range between 0.01 – 0.1; Gradual increase in change in index range between 0.2 – 1.0; Greater
increase in change in index range from 1.1 and above.
20
Annexure 3: Correlation Matrix
GDP
growth rate
Log
(Percapita GDP)
Political
constraints
Poverty
rate
Gini
Inequality
Schedule
Elections
Mid-
Elections
Economic Globalization
GDP growth rate 1.00
Log (Percapita GDP) 0.46 1.00
Political constraints 0.05 0.14 1.00
Poverty rate -0.43 -0.86 -0.18 1.00
Gini Inequality 0.26 0.80 0.01 -0.74 1.00
Schedule Elections -0.10 -0.07 0.09 0.08 0.06 1.00
Mid-elections 0.02 0.15 -0.18 -0.17 0.15 -0.03 1.00
Socioeconomic crisis -0.04 -0.15 -0.23 0.09 -0.37 -0.31 0.09
1 year before elections 0.22 -0.06 0.02 0.08 -0.06 -0.05 -0.32
2 years before elections 0.07 -0.03 0.03 0.00 -0.10 0.29 -0.17
3 years before elections 0.01 0.02 -0.06 -0.07 0.06 -0.18 0.22
4 years before elections 0.02 -0.00 0.24 -0.00 0.09 -0.11 0.22
Socioeconomic
crisis
1 year before
elections
2 years before
elections
3 years before
elections
4 years before
elections
Socioeconomic crisis 1.00
1 year before elections 0.04 1.00
2 years before elections 0.07 -0.17 1.00
3 years before elections -0.13 -0.15 -0.13 1.00
4 years before elections -0.13 -0.15 -0.13 -0.12 1.00
21
Annexure 4: Robustness check – 1: Elections & Economic Globalization equation function
Dependent variable: Dreher‘s Economic Globalization Index
Variables Model 8 Model 9 Model 10 Model 11
Constant
-248.43 *
(19.76)
-251.23 *
(17.73)
-248.63 *
(20.65)
-247.35 *
(17.19)
Schedule Election year
-0.49 **
(0.21)
-0.66 *
(0.20)
-0.49 **
(0.23)
-0.54 **
(0.20)
1 year before Elections 0.10
(0.65) ------ ------ ------
2 years before Elections ------ 1.56 *
(0.50)
------ ------
3 years before Elections
------ ------ 0.02
(0.47) ------
4 years before Elections
------ ------ ------ -0.87
(0.86)
Log (Economic Development)
41.39 * (3.08)
41.60 *
(2.91)
41.40 *
(3.26)
40.88 *
(2.86)
GDP Growth rate
-0.27 * (0.08)
-0.29 *
(0.07)
-0.27 *
(0.08)
-0.26 *
(0.09)
Political Constraints Index
-4.97
(3.55)
-4.91 +
(3.22)
-4.92
(3.50)
-3.84
(3.03)
Poverty Rates 0.63 * (0.09)
0.64 * (0.08)
0.63 * (0.09)
0.63 * (0.07)
Gini Inequality Index
0.41 ** (0.15)
0.45 * (0.13)
0.41 *
(0.14)
0.46 *
(0.14)
Economic & Political Crisis
-1.36 + (0.86)
-1.56 **
(0.69)
-1.34 +
(0.87)
-1.38 ***
(0.83)
R-squared 0.982929 0.985946 0.982915 0.983681 Adjusted R-squared 0.978052 0.981930 0.978033 0.979018 Durbin-Watson statistic 1.820801 2.166064 1.824140 1.865997 Log likelihood -58.27005 -54.67315 -58.28578 -57.43698 F-statistic 201.5293 245.5318 201.3551 210.9731
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.197479 0.450628 0.193503 0.081264
Probability. F 0.6603 0.5077 0.6635 0.7778
Total number of Observations 37 37 37 37 Note: * Significant at 1% confidence level; ** Significant at 5% confidence level *** Significant at 10%
confidence level; + Significant at 15% confidence level. The models are controlled for Heteroskedasticity.
White Heteroskedasticity-Consistent Standard Errors are reported in parenthesis.
22
Annexure 5: Robustness check – 2: Elections & Economic Globalization equation function
Dependent variable: Dreher‘s Economic Globalization Index
Variables Model 12 Model 13
Constant
-244.66 *
(20.31)
-252.81 *
(27.72)
Schedule Election year
-0.47 **
(0.23) ------
1 year before Elections ------ 0.33
(0.72)
2 years before Elections
------ 0.88 +
(0.57)
3 years before Elections ------ 0.62
(0.52)
4 years before Elections ------ 0.16
(1.36)
Log (Economic Development)
40.73 * (3.24)
41.89 *
(4.36)
GDP Growth rate
-0.27 * (0.08)
-0.28 *
(0.09)
Political Constraints Index
-4.81
(3.50)
-4.96
(3.54)
Poverty Rates 0.64 * (0.09)
0.65 * (0.12)
Gini Inequality Index 0.41 * (0.14)
0.39 ** (0.15)
Economic & Political Crisis
-1.46 *** (0.86)
-0.88
(0.95)
Number of Strikes & Lockouts -0.0004 (0.00)
-0.0002 (0.00)
R-squared 0.983070 0.980956 Adjusted R-squared 0.978233 0.972577 Durbin-Watson statistic 1.860615 1.596432 Log likelihood -58.11641 -60.29358 F-statistic 203.2392 117.0690
Total number of Observations 37 37 Note: * Significant at 1% confidence level; ** Significant at 5% confidence level *** Significant at 10%
confidence level; + Significant at 15% confidence level. The models are controlled for Heteroskedasticity.
White Heteroskedasticity-Consistent Standard Errors are reported in parenthesis.
23
Annexure 6: Sensitivity Analysis - Elections & Economic Globalization equation function
Dependent variable: Modified Economic Globalization Index
Variables Model 14 Model 15 Model 16 Model 17
Constant
-5.22 *
(0.57)
-5.18 *
(0.71)
-5.29 *
(0.71)
-5.16 *
(0.48)
Schedule Election year
-0.01 **
(0.00) ------ ------ -0.02 **
(0.01)
Mid-term Election years ------ -0.01
(0.01) ------ ------
1 year before Elections
------ ------ 0.001
(0.02)
0.002
(0.01)
2 years before Elections ------ ------ 0.01
(0.01) 0.03 **
(0.01)
3 years before Elections
------ ------ 0.005
(0.01)
-0.01
(0.01)
4 years before Elections
------ ------ -0.01
(0.03)
-0.03
(0.03)
Log (Economic Development)
0.84 * (0.09)
0.83 *
(0.11)
0.84 *
(0.12)
0.82 *
(0.08)
GDP Growth rate
-0.004 ** (0.00)
-0.004 ***
(0.00)
-0.004 +
(0.00)
-0.004 **
(0.00)
Political Constraints Index
-0.16 ***
(0.09)
-0.19 ****
(0.10)
-0.16 ***
(0.10)
-0.14 +
(0.09)
Poverty Rates 0.01 * (0.00)
0.01 * (0.00)
0.01 * (0.00)
0.01 * (0.00)
Gini Inequality Index
0.01 ** (0.00)
0.01 ** (0.00)
0.01 ***
(0.00)
0.01 **
(0.00)
Economic & Political Crisis
-0.03 *** (0.02)
-0.01
(0.01)
-0.02
(0.01)
-0.03 **
(0.02)
R-squared 0.966560 0.961491 0.961514 0.971873 Adjusted R-squared 0.958489 0.952195 0.946712 0.959497 Durbin-Watson statistic 1.414022 1.178193 1.172264 1.497718 Log likelihood 75.36145 72.75005 72.76130 78.56216 F-statistic 119.7479 103.4381 64.95737 78.52964
Total number of Observations 37 37 37 37 Note: * Significant at 1% confidence level; ** Significant at 5% confidence level *** Significant at 10%
confidence level; + Significant at 15% confidence level. The models are controlled for Heteroskedasticity.
White Heteroskedasticity-Consistent Standard Errors are reported in parenthesis.
24
Graph 1 for Model 6
Coefficients on Election Cycle for Economic Globalization
0.09
0.69
0.97
0.42
-0.49
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
4 years before
elections
3 years before
elections
2 years before
elections
1 year before
elections
election year
Years before schedule elections
Co
eff
icie
nt
va
lue
s
Graph 2 for Model 7
Coefficienton Election Cycle for Economic Globalization (joint)
-0.62
0.05
1.59
0.3
-0.69
-1
-0.5
0
0.5
1
1.5
2
4 years before
election year
3 years before
election year
2 years before
election year
1 year before
election year
Schedule election
year
Years before Schedule election
co
eff
icie
nt
va
lue
s
25
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